Electronic Health Records and Precision Medicine: Enabling Large-Scale Discoveries Using Phenome-Wide Approaches

The goal of Precision Medicine is to provide medical regimes tailored specifically for a given patient’s unique characteristics (e.g., genetics, family history, allergies). Clinical record systems are a valuable data source as they contain many unique facets of patients including their family history of disease, demographics (ethnicity, birth month), comorbidities, medications and laboratory results. Phenome-wide association studies (PheWAS) are studies that harness both the data stored in the Electronic Health Record (EHRs) and another source (e.g., genetic or environmental). PheWAS studies have larger sample sizes (Ns) then traditional epidemiology studies or genome-wide association studies (GWAS). High-throughput exploration of birth month – disease relationships called a SeaWAS (season-wide association study) is an example of a phenome-method that we developed at Columbia University Medical Center. The method explores the relationship between seasonal factors at birth and later-life risk of disease. I will discuss this method along with other methods for utilizing EHR data in the context of precision medicine, especially as a tool to validate the results of biological studies.